Dataset Information

Productivity of public hospitals in Nepal: a data envelopment analysis.

ABSTRACT:

Objectives

Public hospitals in Nepal account for a major share of the total health budget. Therefore, questions are often asked about the performance of these hospitals. Existing measures of performance are limited to historical ratio analyses without any benchmarks. The objective of this study is to explore the trends in inputs, outputs and productivity changes in Nepalese public hospitals from 2011-2012 to 2013-2014.

Setting and participants

The study was conducted among 32 Nepalese public hospitals (23 district level and 9 higher level) for the three fiscal years from 2011-2012 to 2013-2014.

Outcome measures

First, basic ratio analyses were conducted for the input and output measures over the study years. Then, Malmquist productivity change scores were obtained using data envelopment analysis. Aggregated as well as separate analyses were conducted for district level and higher level hospitals.

Results

Real expenditures of the sampled hospitals declined over the 3-year period from an average of US$ 371 000 in year 1 to US$ 368 730 in year 2 and US$ 328680 in year 3. The average aggregated hospital outputs increased marginally from 8276 in 2011-2012 to 8613 in 2013-2014. The total factor productivity of the study hospitals declined by 6.9% annually from 2011-2012 to 2013-2014. Of the total 32 hospitals, productivity increased in only 12 (37.5%) hospitals and declined in the remaining 20 hospitals. The total factor productivity loss was influenced by a decline in technology change, despite an increase in efficiency.

Conclusions

In general, productivity of the study hospitals declined over the study period. Availability and accessibility of accurate, detailed and consistent measures of hospital inputs and outputs is a major challenge for this type of analysis.

SUBMITTER: Silwal PR

PROVIDER: S-EPMC5642787 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Publications

Productivity of public hospitals in Nepal: a data envelopment analysis.

Silwal Pushkar Raj PR Ashton Toni T

BMJ open 20170720 7

<h4>Objectives</h4>Public hospitals in Nepal account for a major share of the total health budget. Therefore, questions are often asked about the performance of these hospitals. Existing measures of performance are limited to historical ratio analyses without any benchmarks. The objective of this study is to explore the trends in inputs, outputs and productivity changes in Nepalese public hospitals from 2011-2012 to 2013-2014.<h4>Setting and participants</h4>The study was conducted among 32 Nepa ...[more]

PMID: 28729314

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Project description:OBJECTIVE:In this study, we assess the performance of public hospitals in Saudi Arabia. We detect the sources of inefficiency and estimate the optimal levels of the resources that provide the current level of health services. We enrich our analysis by employing locations and capacities of the hospitals. DESIGN:We employ data envelopment analysis (DEA) to measure the technical efficiency of 91 public hospitals. We apply the input-oriented Charnes, Cooper and Rhodes, and Banker, Charne, Cooper models under Constant and Variable Returns-to-Scale. The assessment includes four inputs, and six output variables taken from the Ministry of Health databases for 2017. We conducted the assessment via PIM-DEA V.3.2 software. SETTING:Ministry of health-affiliated hospitals in the Kingdom of Saudi Arabia. RESULTS:Findings identified 75.8% (69 of 91) of public hospitals as technically inefficient. The average efficiency score was 0.76, indicating that hospitals could have reduced their inputs by 24% without reduction in health service provision. Small hospitals (efficiency score 0.79) were more efficient than medium-sized and large hospitals. Hospitals in the central region were more efficient (efficiency score 0.83), than those located in other geographical locations. More than half of the hospitals (62.6%) were operating suboptimally in terms of the scale efficiency, implying that to improve efficiency, they need to alter their production capacity. Performance analysis identified overuse of physician's numbers and shortage of health services production, as major causes of inefficiency. CONCLUSION:Most hospitals were technically inefficient and operating at suboptimal scale size and indicate that many hospitals may improve their performance through efficient utilisation of health resources to provide the current level of health services. Changes in the production capacity are required, to facilitate optimal use of medical capacity. The inefficient hospitals could benefit from these findings to benchmarking their system and performance in light of the efficient hospital within their capacity and geographical location.

Project description:BackgroundIn order to measure and analyse the technical efficiency of district hospitals in Ghana, the specific objectives of this study were to (a) estimate the relative technical and scale efficiency of government, mission, private and quasi-government district hospitals in Ghana in 2005; (b) estimate the magnitudes of output increases and/or input reductions that would have been required to make relatively inefficient hospitals more efficient; and (c) use Tobit regression analysis to estimate the impact of ownership on hospital efficiency.MethodsIn the first stage, we used data envelopment analysis (DEA) to estimate the efficiency of 128 hospitals comprising of 73 government hospitals, 42 mission hospitals, 7 quasi-government hospitals and 6 private hospitals. In the second stage, the estimated DEA efficiency scores are regressed against hospital ownership variable using a Tobit model. This was a retrospective study.ResultsIn our DEA analysis, using the variable returns to scale model, out of 128 district hospitals, 31 (24.0%) were 100% efficient, 25 (19.5%) were very close to being efficient with efficiency scores ranging from 70% to 99.9% and 71 (56.2%) had efficiency scores below 50%. The lowest-performing hospitals had efficiency scores ranging from 21% to 30%.Quasi-government hospitals had the highest mean efficiency score (83.9%) followed by public hospitals (70.4%), mission hospitals (68.6%) and private hospitals (55.8%). However, public hospitals also got the lowest mean technical efficiency scores (27.4%), implying they have some of the most inefficient hospitals.Regarding regional performance, Northern region hospitals had the highest mean efficiency score (83.0%) and Volta Region hospitals had the lowest mean score (43.0%).From our Tobit regression, we found out that while quasi-government ownership is positively associated with hospital technical efficiency, private ownership negatively affects hospital efficiency.ConclusionsIt would be prudent for policy-makers to examine the least efficient hospitals to correct widespread inefficiency. This would include reconsidering the number of hospitals and their distribution, improving efficiency and reducing duplication by closing or scaling down hospitals with efficiency scores below a certain threshold. For private hospitals with inefficiency related to large size, there is a need to break down such hospitals into manageable sizes.

Dataset Information

Productivity of public hospitals in Nepal: a data envelopment analysis.

Objectives

Setting and participants

Outcome measures

Results

Conclusions

Publications

Productivity of public hospitals in Nepal: a data envelopment analysis.

Similar Datasets

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